Search results for: embedded applications

Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

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Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

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Authors: M. Yousefi, N. Nasirzadeh

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In this paper, dynamic comparator structure employing two methods for power consumption reduction with applications in low-power high-speed analog-to-digital converters have been presented. The proposed comparator has low consumption thanks to power reduction methods. They have the ability for offset adjustment. The comparator consumes 14.3 μW at 100 MHz which is equal to 11.8 fJ. The comparator has been designed and simulated in 180 nm CMOS. Layouts occupy 210 μm².

Keywords: efficiency, comparator, power, low

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: Rubaiyat Jahan

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This paper reports some findings of a study on the issues related to teacher autonomy in the Bangladeshi school contexts, and data of this research was collected from fourteen practicing English teachers of Bangladesh through semi structured interviews. The theoretical underpinning of teacher autonomy, on an apparent note, focuses on the behavioral aspects of teacher autonomy hence emphasizing mostly on the teachers’ capacity for self-directed acts of teaching and self-directed acts of professional development. Yet, a contemporary literature survey of teacher autonomy seems to be concerned more on the political interpretations of teacher autonomy. Thus, autonomous teachers are expected to generate their personal theories of teaching from their practices. The idea of personal theories of practice upholds the view that along with the teaching, teachers need to engage themselves in various classroom based research with a view to theorising from their practices. The findings of this research indicate enormous evidence of behavioral aspects of teacher autonomy. As the data of this research suggests, the participant teachers’ understanding of classroom situations, their reflections on the situational realities and opting for classroom decisions on the basis of those realizations are some good examples of teacher autonomy. Also, a few teachers’ stated teaching practices seem to reflect, though in a subtle way, their effort of outlining context embedded personal theories of teaching. This paper has got one significant pedagogical implication for the teacher education. Any teacher education must promote the conditions and capabilities for the present and prospective teachers for the role of theorisers in addition to develop their professional, procedural, and personal knowledge base.

Keywords: personal theories of practice, self-directed acts of professional development, self-directed acts of teaching, teacher autonomy

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Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

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To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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Authors: Efuwape Bamidele Michael, Efuwape Oluwabunmi Asake

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Nigeria has some deep rural environments that seem secluded from most of the technological amenities for convenient living and learning. Most schools in such environments are yet to be captured in the educational applications of technological facilities. The study explores the facilitation of basic technology instructions with micro-learning and gamification among students in rural Junior Secondary Schools in the Ipokia Local Government Area (LGA) of Ogun state. The study employed a quasi-experimental design, specifically the pre-test and post-test control group design. The study population comprised all Junior Secondary School students in the LGA. Four Junior Secondary Schools in the LGA were randomly selected for the study and classified into two experimental and two control groups. A total sample of 156 students participated in the study. Basic Technology Achievement Test and Junior School Students’ Attitudinal Scale were instruments used for data collection in the study with reliability coefficients of 0.87 and 0.83, respectively. Five hypotheses guided the study and were tested using Analysis of covariance (ANCOVA) at a 0.05 level of significance. Findings from the study established significant marginal differences in students’ academic performance (F = 644.301; p = .000), learning retention (F = 583.335; p = .000), and attitude towards learning basic technology (F = 491.226; p = .000) between the two groups in favour of the experimental group exposed to micro-learning and gamification. As a recommendation, adequate provisions for inclusive educational practices with technological applications should be ensured for all children irrespective of location within the country, especially to encourage effective learning in rural schools.

Keywords: inclusive education, educational technology, basic technology students, rural areas in Nigeria, micro-learning, gamification

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Authors: Reza Soleimanpour, Ching Tai Ng

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Fibre-composites are widely used in various structures due to their attractive properties such as higher stiffness to mass ratio and better corrosion resistance compared to metallic materials. However, one serious weakness of this composite material is delamination, which is a subsurface separation of laminae. A low level of this barely visible damage can cause a significant reduction in residual compressive strength. In the last decade, the application of guided waves for damage detection has been a topic of significant interest for many researches. Among all guided wave techniques, nonlinear guided wave has shown outstanding sensitivity and capability for detecting different types of damages, e.g. cracks and delaminations. So far, most of researches on applications of nonlinear guided wave have been dedicated to isotropic material, such as aluminium and steel, while only a few works have been done on applications of nonlinear characteristics of guided waves in anisotropic materials. This study investigates the nonlinear interactions of the fundamental antisymmetric lamb wave (A0) with delamination in composite laminates using three-dimensional (3D) explicit finite element (FE) simulations. The nonlinearity considered in this study arises from interactions of two interfaces of sub-laminates at the delamination region, which generates contact acoustic nonlinearity (CAN). The aim of this research is to investigate the phenomena of CAN in composite laminated beams by a series of numerical case studies. In this study interaction of fundamental antisymmetric lamb wave with delamination of different sizes are studied in detail. The results show that the A0 lamb wave interacts with the delaminations generating CAN in the form of higher harmonics, which is a good indicator for determining the existence of delaminations in composite laminates.

Keywords: contact acoustic nonlinearity, delamination, fibre reinforced composite beam, finite element, nonlinear guided waves

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Aneesh Joshi, Sagil James

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Cold Spray (CS) process is deposition of solid particles over a substrate above a certain critical impact velocity. Unlike thermal spray processes, CS process does not melt the particles thus retaining their original physical and chemical properties. These characteristics make CS process ideal for various engineering applications involving metals, polymers, ceramics and composites. The bonding mechanism involved in CS process is extremely complex considering the dynamic nature of the process. Though CS process offers great promise for several engineering applications, the realization of its full potential is limited by the lack of understanding of the complex mechanisms involved in this process and the effect of critical process parameters on the deposition efficiency. The goal of this research is to understand the complex nanoscale mechanisms involved in CS process. The study uses Molecular Dynamics (MD) simulation technique to understand the material deposition phenomenon during the CS process. Impact of a single crystalline copper nanoparticle on copper substrate is modelled under varying process conditions. The quantitative results of the impacts at different velocities, impact angle and size of the particles are evaluated using flattening ratio, von Mises stress distribution and local shear strain. The study finds that the flattening ratio and hence the quality of deposition was highest for an impact velocity of 700 m/s, particle size of 20 Å and an impact angle of 90°. The stress and strain analysis revealed regions of shear instabilities in the periphery of impact and also revealed plastic deformation of the particles after the impact. The results of this study can be used to augment our existing knowledge in the field of CS processes.

Keywords: cold spray process, molecular dynamics simulation, nanoparticles, particle impact

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Authors: Suresh Kumar Reddy Narala, Rakesh Kumar Gunda

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In modern industry, mechanical parts are subjected to friction and wear, leading to heat generation, which affects the reliability, life and power consumption of machinery. To overcome the tribological losses due to friction and wear, a significant portion of lubricant with high viscous properties allows very smooth relative motion between two sliding surfaces. Advancement in modern tribology has facilitated the use of applying solid lubricants in various industrial applications. Solid lubricant additives with high viscous thin film formation between the sliding surfaces can adequately wet and adhere to a work surface. In the present investigation, an attempt has been made to investigate and evaluate the tribological studies of various solid lubricants like MoS¬2, graphite, and boric acid at different sliding conditions. The base oil used in this study was SAE 40 oil with a viscosity of 220 cSt at 400C. The tribological properties were measured on pin-on-disc tribometer. An experimental set-up has been developed for effective supply of solid lubricants to the pin-disc interface zone. The results obtained from the experiments show that the friction coefficient increases with increase in applied load for all the considered environments. The tribological properties with MoS2 solid lubricant exhibit larger load carrying capacity than that of graphite and boric acid. The present research work also contributes to the understanding of the behavior of film thickness distribution of solid lubricant using potential contact technique under different sliding conditions. The results presented in this research work are expected to form a scientific basis for selecting the best solid lubricant in various industrial applications for possible minimization of friction and wear.

Keywords: friction, wear, temperature, solid lubricant

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Authors: Saravanan Govindaraju, Kyusik Yun

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The purpose of this study is to develop the chitosan doped curcumin gold cluster nanofiber for wound healing and skin cancer drug delivery applications. Chitosan is a typical marine polysaccharide composed of glucosamine and n-acetyl glucosamine biodegradable and biocompatible polymer. Curcumin is a natural bioactive molecule obtained from Curcuma longo, it mostly occurs in some Asian countries like India and China. It has naturally antioxidant, antimicrobial, wound healing and anticancer property. Due to this advantage, we prepared a combination of natural polymer chitosan with Curcumin and gold nanocluster nanofiber (CH-CUR-AuNCs nanofibers). The prepared nanofiber was characterized by using Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Antibacterial studies were performed with E.coli and S.aureus. Antioxidant assay, drug release test, and cytotoxicity will be evaluated. Prepared nanofiber emits low intensity of red fluorescent. The FTIR confirm the presence of chitosan and Curcumin in the nanofiber. In vitro study clearly shows the antibacterial activity against the gram negative and gram positive bacteria. Particularly, synthesised nanofibers provide better antibacterial activity against gram negative than gram positive. Cytotoxicity study also provides better killing rate in cancer cell, biocompatible with normal cell. Prepared CH-CUR-AuNCs nanofibers provide the better killing rate to bacterial strains and cancer cells. Finally, prepared nanofiber can be possible to use for wound healing dressing, patch for skin cancer and other biomedical applications.

Keywords: curcumin, chitosan, gold clusters, nanofibers

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Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

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Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

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Authors: Ibrahim Rassoul, E-K. Si Ahmed

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The growth, deformation, and detachment of fluid droplets adherent to solid substrates is a problem of fundamental interest with numerous practical applications. Specific interest in this proposal is the problem of a droplet on a fibrous, hydrophobic substrate subjected to body or external forces (gravity, convection). The past decade has seen tremendous advances in proton exchange membrane fuel cell (PEMFC) technology. However, there remain many challenges to bring commercially viable stationary PEMFC products to the market. PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On the one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause 'flooding' (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The aim of this work is to investigate the stability of a liquid water droplet emerging form a GDL pore, to gain fundamental insight into the instability process leading to detachment. The approach will combine analytical and numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, water droplet, gas diffusion layer, contact angle, surface tension

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Authors: Silipa Halofaki, Devi R. Seenivasagam, Prashant Bijay, Kritin Singh, Rajeshkannan Ananthanarayanan

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This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria, such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality, were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.

Keywords: literature review, productivity, small and medium sized enterprises-SMEs, work system design

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Authors: Sharvare Palwai, Padmaja Guggilla

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Smart materials, also called as responsive materials, undergo reversible physical or chemical changes in their properties as a consequence of small environmental variations. They can respond to a single or multiple stimuli such as stress, temperature, moist, electric or magnetic fields, light, or chemical compounds. Hence smart materials are the basis of many applications, including biosensors and transducers, particularly electroactive polymers. As the polymers exhibit good flexibility, high transparency, easy processing, and low cost, they would be promising for the sensor material. Polyvinylidene Fluoride (PVDF), being a ferroelectric polymer, exhibits piezoelectric and pyro electric properties. Pyroelectric materials convert heat directly into electricity, while piezoelectric materials convert mechanical energy into electricity. These characteristics of PVDF make it useful in biosensor devices and batteries. However, the influence of nanoparticle fillers such as Lithium Tantalate (LiTaO₃/LT), Potassium Niobate (KNbO₃/PN), and Zinc Titanate (ZnTiO₃/ZT) in polymer films will be studied comprehensively. Developing advanced and cost-effective biosensors is pivotal to foresee the fullest potential of polymer based wireless sensor networks, which will further enable new types of self-powered applications. Finally, nanocomposites films with best set of properties; the sensory elements will be designed and tested for their performance as electric generators under laboratory conditions. By characterizing the materials for their optical properties and investigate the effects of doping on the bandgap energies, the science in the next-generation biosensor technologies can be advanced.

Keywords: polyvinylidene fluoride, PVDF, lithium tantalate, potassium niobate, zinc titanate

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Authors: Ouahiba Bechiri, Mostefa Abbessi

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In recent year, polyoxometallates are intensely being explored because of their applications as new materiels, structural aesthetics, catalysts, and biologically active compounds. heteropolyanions of general formulae [X2M18O62] n- (X= heteroatom, e.g. P, Si) and (M=W, Mo), known as Dawson-type anions, constitue a special class of polyoxometallate compounds. In this present work, cobalt substituted heteropolyanion Dawson-type [HP2W15Mo3CoO61] were synthesized and characterized by IR spectroscopy, 31 P NMR, cyclic voltammetry.

Keywords: heteropolyanions, nanomaterials, Dawson-type, characterization

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Authors: Jiajia Yao, GuanLin Wu, Fang liu, JunShuai Xue, JinCheng Zhang, Yue Hao

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Due to its outstanding material properties like high thermal conductivity and ultra-wide bandgap, Aluminum nitride (AlN) has the promising potential to provide high breakdown voltage and high output power among III-nitrides for various applications in electronics and optoelectronics. This work presents material growth and characterization of strained channel Aluminum nitride/Gallium nitride (AlN/GaN) heterostructures grown by plasma-assisted molecular beam epitaxy (PA-MBE) on AlN-on-sapphire templates. To improve the crystal quality and manifest the ability of the PA-MBE approach, a thick AlN buffer with a thickness of 180 nm is first grown on AlN template, which acts as a back-barrier to enhance the breakdown characteristic and isolates the leakage path existing in the interface between AlN epilayer and AlN template, as well as improve the heat dissipation. The grown AlN buffer features a root-mean-square roughness of 0.2 nm over a scanned area of 2×2 µm2 measured by atomic force microscopy (AFM), and exhibits full-width at half-maximum of 95 and 407 arcsec for the (002) and (102) plane the X-ray rocking curve, respectively, tested by high resolution x-ray diffraction (HR-XRD). With a thin and strained GaN channel, the electron mobility of 294 cm2 /Vs. with a carrier concentration of 2.82×1013 cm-2 at room temperature is achieved in AlN/GaN double-channel heterostructures, and the depletion capacitance is as low as 14 pF resolved by the capacitance-voltage, which indicates the promising opportunities for future applications in next-generation high temperature, high-frequency and high-power electronics with a further increased electron mobility by optimization of heterointerface quality.

Keywords: AlN/GaN, HEMT, MBE, homoepitaxy

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Authors: Reyhan Ozbask, Emek Moroydor Derin, Mustafa Dogu

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There are a limited number of global companies in the world that manufacture and commercially offer thermoplastic composite prepregs in accordance with aerospace requirements. High-performance thermoplastic materials supplied for aerospace structural applications are PEEK (polyetheretherketone), PPS (polyphenylsulfite), PEI (polyetherimide), and PEKK (polyetherketoneketone). Among these, PEEK is the raw material used in the first applications and has started to become widespread. However, the use of these thermoplastic raw materials in composite production is very difficult due to their high processing temperatures and impregnation difficulties. This study, it is aimed to develop carbon fiber-reinforced thermoplastic PEEK composites that comply with the requirements of the aviation industry that are superior mechanical properties as well as being lightweight. Therefore, it is aimed to obtain high-performance thermoplastic composite materials with improved interface properties by using the sizing method (suspension development through chemical synthesis and functionalization), to optimize the production process. The use of boron nitride nanotube as a bonding agent by modifying its surface constitutes the original aspect of the study as it has not been used in composite production with high-performance thermoplastic materials yet. For this purpose, laboratory-scale studies on the application of thermoplastic compatible sizing will be carried out in order to increase the fiber-matrix interfacial adhesion. The method respectively consists of the selection of appropriate sizing type, laboratory-scale carbon fiber (CF) / poly ether ether ketone (PEEK) polymer interface enhancement studies, manufacturing of laboratory-scale BNNT coated CF/PEEK woven prepreg composites and their tests.

Keywords: carbon fiber reinforced composite, interface enhancement, boron nitride nanotube, thermoplastic composite

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Authors: Bekan Bogale, Tsegaye Girma Asere, Tilahun Yai, Fekadu Melak

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Aims: To study photocatalytic degradation of methylene blue dye on cuprous oxide/graphene nanocomposite. Background: Cuprous oxide (Cu2O) nanoparticles are among the metal oxides that demonstrated photocatalytic activity. However, the stability of Cu2O nanoparticles due to the fast recombination rate of electron/hole pairs remains a significant challenge in their photocatalytic applications. This, in turn, leads to mismatching of the effective bandgap separation, tending to reduce the photocatalytic activity of the desired organic waste (MB). To overcome these limitations, graphene has been combined with cuprous oxides, resulting in cuprous oxide/graphene nanocomposite as a promising photocatalyst. Objective: In this study, Cu2O/graphene nanocomposite was synthesized and evaluated for its photocatalytic performance of methylene blue (MB) dye degradation. Method: Cu2O/graphene nanocomposites were synthesized from graphite powder and copper nitrate using the facile sol-gel method. Batch experiments have been conducted to assess the applications of the nanocomposites for MB degradation. Parameters such as contact time, catalyst dosage, and pH of the solution were optimized for maximum MB degradation. The prepared nanocomposites were characterized by using UV-Vis, FTIR, XRD, and SEM. The photocatalytic performance of Cu2O/graphene nanocomposites was compared against Cu2O nanoparticles for cationic MB dye degradation. Results: Cu2O/graphene nanocomposite exhibits higher photocatalytic activity for MB degradation (with a degradation efficiency of 94%) than pure Cu2O nanoparticles (67%). This has been accomplished after 180 min of irradiation under visible light. The kinetics of MB degradation by Cu2O/graphene composites can be demonstrated by the second-order kinetic model. The synthesized nanocomposite can be used for more than three cycles of photocatalytic MB degradation. Conclusion: This work indicated new insights into Cu2O/graphene nanocomposite as high-performance in photocatalysis to degrade MB, playing a great role in environmental protection in relation to MB dye.

Keywords: methylene blue, photocatalysis, cuprous oxide, graphene nanocomposite

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Ghada S. Ellithy, John. W. Murphy, Maureen K. Corcoran

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Erosion rate of soils during a levee or dam overtopping event is a major component in risk assessment evaluation of breach time and downstream consequences. The mechanism and evolution of dam or levee breach caused by overtopping erosion is a complicated process and difficult to measure during overflow due to accessibility and quickly changing conditions. In this paper, the results of a flume erosion tests are presented and discussed. The tests are conducted on a coarse-grained material with a median grain size D50 of 5 mm in a 1-m (3-ft) wide flume under varying flow rates. Each test is performed by compacting the soil mix r to its near optimum moisture and dry density as determined from standard Proctor test in a box embedded in the flume floor. The box measures 0.45 m wide x 1.2 m long x 0.25 m deep. The material is tested several times at varying hydraulic loading to determine the erosion rate after equal time intervals. The water depth, velocity are measured at each hydraulic loading, and the acting bed shear is calculated. A shallow water lidar (SWL) system was utilized to record the progress of soil erodibility and water depth along the scanned profiles of the tested box. SWL is a non-contact system that transmits laser pulses from above the water and records the time-delay between top and bottom reflections. Results from the SWL scans are compared with before and after manual measurements to determine the erosion rate of the soil mix and other erosion parameters.

Keywords: coarse-grained materials, erosion rate, LIDAR system, soil erosion

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Authors: Matthew Korey, Jeffrey Youngblood, John Howarter

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Background and Significance: Tannic acid (TA) is a bio-based high molecular weight organic, aromatic molecule that has been found to increase thermal stability and flame retardancy of many polymer matrices when used as an additive. Although it is biologically sourced, TA is a pollutant in industrial wastewater streams, and there is a desire to find applications in which to downcycle this molecule after extraction from these streams. Additionally, epoxy thermosets have revolutionized many industries, but are too flammable to be used in many applications without additives which augment their flame retardancy (FR). Many flame retardants used in epoxy thermosets are synthesized from petroleum-based monomers leading to significant environmental impacts on the industrial scale. Many of these compounds also have significant impacts on human health. Various bio-based modifiers have been developed to improve the FR of the epoxy resin; however, increasing FR of the system without tradeoffs with other properties has proven challenging, especially for TA. Methodologies: In this work, TA was incorporated into the thermoset by use of solvent-exchange using methyl ethyl ketone, a co-solvent for TA, and epoxy resin. Samples were then characterized optically (UV-vis spectroscopy and optical microscopy), thermally (thermogravimetric analysis and differential scanning calorimetry), and for their flame retardancy (mass loss calorimetry). Major Findings: Compared to control samples, all samples were found to have increased thermal stability. Further, the addition of tannic acid to the polymer matrix by the use of solvent greatly increased the compatibility of the additive in epoxy thermosets. By using solvent-exchange, the highest loading level of TA found in literature was achieved in this work (40 wt%). Conclusions: The use of solvent-exchange shows promises for circumventing the limitations of TA in epoxy.

Keywords: sustainable, flame retardant, epoxy, tannic acid

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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Authors: Kayode A. Olaniyi, Adeola A. Ogunleye, Tola M. Osifeko

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Electric Vehicles (EV) appear to be gaining increasing patronage as a feasible alternative to Internal Combustion Engine Vehicles (ICEVs) for having low emission and high operation efficiency. The EV energy storage systems are required to handle high energy and power density capacity constrained by limited space, operating temperature, weight and cost. The choice of strategies for energy storage evaluation, monitoring and control remains a challenging task. This paper presents review of various energy storage technologies and recent researches in battery evaluation techniques used in EV applications. It also underscores strategies for the hybrid energy storage management and control schemes for the improvement of EV stability and reliability. The study reveals that despite the advances recorded in battery technologies there is still no cell which possess both the optimum power and energy densities among other requirements, for EV application. However combination of two or more energy storages as hybrid and allowing the advantageous attributes from each device to be utilized is a promising solution. The review also reveals that State-of-Charge (SoC) is the most crucial method for battery estimation. The conventional method of SoC measurement is however questioned in the literature and adaptive algorithms that include all model of disturbances are being proposed. The review further suggests that heuristic-based approach is commonly adopted in the development of strategies for hybrid energy storage system management. The alternative approach which is optimization-based is found to be more accurate but is memory and computational intensive and as such not recommended in most real-time applications.

Keywords: battery state estimation, hybrid electric vehicle, hybrid energy storage, state of charge, state of health

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Authors: D. Mehdizadeh, M. Rahimian, M. Eskandari-Ghadi

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This article is concerned with the determination of the static interaction of a vertically loaded rigid circular disc embedded at the interface of a horizontal layer sandwiched in between two different transversely isotropic half-spaces called as tri-material full-space. The axes of symmetry of different regions are assumed to be normal to the horizontal interfaces and parallel to the movement direction. With the use of a potential function method, and by implementing Hankel integral transforms in the radial direction, the government partial differential equation for the solely scalar potential function is transformed to an ordinary 4th order differential equation, and the mixed boundary conditions are transformed into a pair of integral equations called dual integral equations, which can be reduced to a Fredholm integral equation of the second kind, which is solved analytically. Then, the displacements and stresses are given in the form of improper line integrals, which is due to inverse Hankel integral transforms. It is shown that the present solutions are in exact agreement with the existing solutions for a homogeneous full-space with transversely isotropic material. To confirm the accuracy of the numerical evaluation of the integrals involved, the numerical results are compared with the solutions exists for the homogeneous full-space. Then, some different cases with different degrees of material anisotropy are compared to portray the effect of degree of anisotropy.

Keywords: transversely isotropic, rigid disc, elasticity, dual integral equations, tri-material full-space

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Authors: Michael Fusi Ligaliga

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Peace and Conflict Studies (PACS), despite being a new pedagogical discipline, is a growing interdisciplinary academic field that has expanded its presence from the traditional lens of war, conflict, and violence to addressing various social issues impacting society. Family and domestic violence (FDV) has seldom been explored through the PACS lens despite some studies showing that “on average, nearly 20 people per minute are physically abused by an intimate partner in the United States. Over one year, this equates to more than 10 million women and men.” In the Pacific, FDV rates are some of the highest in the world. The friction caused by cultural practices reinforcing patriarchy and male impunity, compounded by historical colonial experiences, as well as the impact of Christianity on the Pacific region, creates a complex social landscape when thinking about and addressing FDV in the Pacific. This paper seeks to re-examine Johan Galtung’s violence triangle (GVT) theory and its application to understanding FDV in the Pacific. Galtung argues that there are three forms of violence – direct, structural, and cultural. Direct violence (DV) is behaviors that threaten life itself or diminishes the ability of a person to meet his or her basic needs. This form of violence is visible because it is manifested in behaviors such as killing, maiming, sexual assault, etc. Structural violence (SV) exists when people do not get equal access to goods and services (health, education, justice) that enable them to reach their full potential. When ideologies embedded in cultural norms and practices are used to justify and advocate acts of violence by shifting the moral parameters from being wrong to right or acceptable, this, according to Galtung, is referred to as Cultural violence (CV).

Keywords: direct violence, cultural violence, structural violence, indigenous peacebuilding, samoa

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Authors: Mahamad Yousif, Eoin Cunningham, Beatrice Smyth

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Every year ~6 million tonnes of feathers are produced globally. Due to feathers’ low density and possible contamination with pathogens, their disposal causes health and environmental problems. The extraction of keratin, which represents >90% of feathers’ dry weight, could offer a solution due to its wide range of applications in the food, medical, cosmetics, and biopolymer industries. One of these applications is the production of biofilms which can be used for packaging, edible films, drug delivery, wound healing etc. Several studies in the last two decades investigated keratin film production and its properties. However, the effects of many parameters on the properties of the films remain to be investigated including the extraction method, crosslinker type and concentration, and the film production method. These parameters were investigated in this study. Keratin was extracted from chicken feathers using two methods, alkaline extraction with 0.5 M NaOH at 80 °C or sulphitolysis extraction with 0.5 M sodium sulphite, 8 M urea, and 0.25-1 g sodium dodecyl sulphate (SDS) at 100 °C. The extracted keratin was mixed with different types and concentrations of plasticizers (glycerol and polyethylene glycol) and crosslinkers (formaldehyde (FA), glutaraldehyde, cinnamaldehyde, glyoxal, and 1,4-Butanediol diglycidyl ether (BDE)). The mixtures were either cast in a mould or compression moulded to produce films. For casting, keratin powder was initially dissolved in water to form a 5% keratin solution and the mixture was dried in an oven at 60 °C. For compression moulding, 10% water was added and the compression moulding temperature and pressure were in the range of 60-120 °C and 10-30 bar. Finally, the tensile properties, solubility, and transparency of the films were analysed. The films prepared using the sulphitolysis keratin had superior tensile properties to the alkaline keratin and formed successfully with lower plasticizer concentrations. Lowering the SDS concentration from 1 to 0.25 g/g feathers improved all the tensile properties. All the films prepared without crosslinkers were 100% water soluble but adding crosslinkers reduced solubility to as low as 21%. FA and BDE were found to be the best crosslinkers increasing the tensile strength and elongation at break of the films. Higher compression moulding temperature and pressure lowered the tensile properties of the films; therefore, 80 °C and 10 bar were considered to be the optimal compression moulding temperature and pressure. Nevertheless, the films prepared by casting had higher tensile properties than compression moulding but were less transparent. Two optimal films, prepared by film casting, were identified and their compositions were: (a) Sulphitolysis keratin, 20% glycerol, 10% FA, and 10% BDE. (b) Sulphitolysis keratin, 20% glycerol, and 10% BDE. Their tensile strength, elongation at break, Young’s modulus, solubility, and transparency were: (a) 4.275±0.467 MPa, 86.12±4.24%, 22.227±2.711 MPa, 21.34±1.11%, and 8.57±0.94* respectively. (b) 3.024±0.231 MPa, 113.65±14.61%, 10±1.948 MPa, 25.03±5.3%, and 4.8±0.15 respectively. A higher value indicates that the film is less transparent. The extraction method, film composition, and production method had significant influence on the properties of keratin films and should therefore be tailored to meet the desired properties and applications.

Keywords: compression moulding, crosslinker, film casting, keratin, plasticizer, solubility, tensile properties, transparency

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: S. Naderizadeh, A. Athanassiou, I. S. Bayer

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This work describes a layer-by-layer spraying method to produce a non-wetting coating, based on thermoplastic polyurethane (TPU) and silica nanoparticles (Si-NPs). The main purpose of this work was to transform a hydrophilic polymer to superhydrophobic coating. The contact angle of pure TPU was measured about 77˚ ± 2, and water droplets did not roll away upon tilting even at 90°. But after applying a layer of Si-NPs on top of this, not only the contact angle increased to 165˚ ± 2, but also water droplets can roll away even below 5˚ tilting. The most important restriction in this study was the weak interfacial adhesion between polymer and nanoparticles, which had a bad effect on durability of the coatings. To overcome this problem, we used a very thin layer of graphene nanoplatelets (GNPs) as an interlayer between TPU and Si-NPs layers, followed by thermal treatment at 150˚C. The sample’s morphology and topography were characterized by scanning electron microscopy (SEM), EDX analysis and atomic force microscopy (AFM). It was observed that Si-NPs embedded into the polymer phase in the presence of GNPs layer. It is probably because of the high surface area and considerable thermal conductivity of the graphene platelets. The contact angle value for the sample containing graphene decreased a little bit respected to the coating without graphene and reached to 156.4˚ ± 2, due to the depletion of the surface roughness. The durability of the coatings against abrasion was evaluated by Taber® abrasion test, and it was observed that superhydrophobicity of the coatings remains for a longer time, in the presence of GNPs layer. Due to the simple fabrication method and good durability of the coating, this coating can be used as a durable superhydrophobic coating for metals and can be produced in large scale.

Keywords: graphene, silica nanoparticles, superhydrophobicity, thermoplastic polyurethane

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Authors: Debarati Bhaumik, Diptish Dey

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Multilevel models, increasingly deployed in industries such as insurance, food production, and entertainment within functions such as marketing and supply chain management, need to be transparent and ethical. Applications usually result in binary classification within groups or hierarchies based on a set of input features. Using open-source datasets, we demonstrate that popular explainability methods, such as SHAP and LIME, consistently underperform inaccuracy when interpreting these models. They fail to predict the order of feature importance, the magnitudes, and occasionally even the nature of the feature contribution (negative versus positive contribution to the outcome). Besides accuracy, the computational intractability of SHAP for binomial classification is a cause of concern. For transparent and ethical applications of these hierarchical statistical models, sound audit frameworks need to be developed. In this paper, we propose an audit framework for technical assessment of multilevel regression models focusing on three aspects: (i) model assumptions & statistical properties, (ii) model transparency using different explainability methods, and (iii) discrimination assessment. To this end, we undertake a quantitative approach and compare intrinsic model methods with SHAP and LIME. The framework comprises a shortlist of KPIs, such as PoCE (Percentage of Correct Explanations) and MDG (Mean Discriminatory Gap) per feature, for each of these three aspects. A traffic light risk assessment method is furthermore coupled to these KPIs. The audit framework will assist regulatory bodies in performing conformity assessments of AI systems using multilevel binomial classification models at businesses. It will also benefit businesses deploying multilevel models to be future-proof and aligned with the European Commission’s proposed Regulation on Artificial Intelligence.

Keywords: audit, multilevel model, model transparency, model explainability, discrimination, ethics

Procedia PDF Downloads 87